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DBMS > Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. PieCloudDB

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Data Explorer vs. PieCloudDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPieCloudDB  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully managed big data interactive analytics platformA cloud-native analytic database platform with new technologoy for elastic MPP
Primary database modelDocument storeRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.25
Rank#304  Overall
#138  Relational DBMS
Websitecloud.google.com/­datastoreazure.microsoft.com/­services/­data-explorerwww.openpie.com
Technical documentationcloud.google.com/­datastore/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGoogleMicrosoftOpenPie
Initial release20082019
Current releasecloud service with continuous releases2.1, January 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Server operating systemshostedhostedhosted
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes, details hereyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyes
Secondary indexesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query language (GQL)Kusto Query Language (KQL), SQL subsetyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
CLI Client
JDBC
ODBC
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
PL/SQL
Python
R
Server-side scripts infoStored proceduresusing Google App EngineYes, possible languages: KQL, Python, Ruser defined functions
TriggersCallbacks using the Google Apps Engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using Paxosyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud DataflowSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Azure Active Directory AuthenticationUser Roles and pluggable authentication with full SQL Standard
More information provided by the system vendor
Google Cloud DatastoreMicrosoft Azure Data ExplorerPieCloudDB
Specific characteristicsPieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
» more
Competitive advantagesExtreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
» more
Typical application scenariosPieCloudDB is ideal for Data mining applications that require extreme scalability...
» more
Key customersSail-Cloud China Shipbuilding Group Haizhou System Soochow Securities ​etc.,
» more
Licensing and pricing modelsPieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment;...
» more

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Google Cloud DatastoreMicrosoft Azure Data ExplorerPieCloudDB
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